Communication channels typically exhibit low pass filter effects that disproportionately attenuate high-frequency signal components. These effects can vary from one channel to the next, and can vary over time in a given channel. Adaptive receive equalization schemes are therefore used in high-speed communication links to compensate for all or part of the distortion imposed by the channel.
The amount of channel-induced distortion appearing on any particular bit in a serial data signal is pattern dependent. This pattern dependency owes to the fact that different data patterns have different spectral content, and are thus affected differently by the channel transfer function. As a first-order approximation for a typical channel, the higher the frequency, the greater the attenuation.
Equalization refers generally to processes for emphasizing or attenuating a selected frequency or frequencies of a signal, often to compensate for frequency-specific attenuation of the signal. Equalization schemes can be “adaptive,” in which case the equalization parameters may be dynamically adjusted to account for variables that affect the communication channel, including process variations and fluctuations in temperature, supply voltage, and the noise environment. Many of these adaptive equalization schemes require sensitive analog circuitry and/or additional samplers that significantly increase system complexity, implementation difficulty, and power requirements. There is therefore a need for efficient adaptive receiver equalization systems and methods that are more easily implemented and verified, with reduced power penalty.